Introduction - Semi-quantitative Approaches for Landslide Assessment and Prediction - page 47

Vecchia (1978) proposed the terrain index for the stability of hill slope that includes
numerical rating for lithology, altitude, slope and friction along the potential failure
planes. Pachuri et al.

cation and landslide
susceptibility mapping in Yamuna valley region of Garhwal Himalaya based on
aerial photographs (1:40,000), Landsat Images (1:2,50,000) and topographic maps
(1:50,000). In the Himalaya, landslide zonation map has been attempted by
Majumder (1980) Chatterjee (1986), Gupta (1998), Gairola and Shukla (1990),
Sharan (1992), Chandra (1992), Sharma et al. (1996). The Landslide Hazard
Mapping and Risk Assessment (LHRA) was attempted by Fiener in (1999). He
considered nine factors i.e. lithology, degree of weathering, structure, slope con-
dition, hydrology, erosion, physical properties, land use and land cover and slope
history for the purpose of hazard assessment. Champati Roy et al. (1997) prepared
landslide hazard zonation map on the basis of information value method of an area
in Chamoli district near Pipalkota town using aerial photographs and IRS LISS-II
data. The SINMAP (Stability Index Mapping) was studied by Hammond et al.
( 1992 ), Montgomery and Dietrich ( 1994 ). Swanston and Dyrness (1973), Dietrich
and Dunne (1978), Sidle et al. (1985) concluded that in the forested steep slope
region, shallow landslides are dominant erosional processes. Bergin et al. ( 1995 ),
Sidle et al. (1985), Royster (1979) suggested the reforestation and improved road
drainage as the most important slope stabilization strategies and such strategies
received considerable attention from Cruz and Reyes (2000).
The landslide hazard and risk analysis with the help of the geotechnical model,
logistic regression model and the safety factor was done by Gokceoglu et al. ( 2000 ),
Romeo (2000), Carro et al. (2003), Shou and Wang (2003), Zhou et al. (2003),
Atkinson and Massari ( 1998 ), Dai et al. (2001), Dai and Lee ( 2002 ), and Ohlmacher
and Davis (2003). Rowbothan and Dudycha ( 1998 ), Jibson et al. ( 2000 ), Luzi et al.
(2000), Praise and Jibson ( 2000 ), Rautelal and Lakheraza ( 2000 ), Baeza and
Corominas (2001), Lee and Min (2001), Temesgen et al. (2001), Clerici et al.
(2002), Donati and Turrini ( 2002 ), Lee et al. (2002a, b), Rece and Capolongo
(2002), Zhou et al. ( 2002 ), and Lee and Choi ( 2003 ) have applied the probabilistic
model for landslide risk and hazard analysis.
Shasko and Keller (1991), Guzzetti et al. ( 1999a , b , c ) discussed the possibility
and feasibility of integrating sophisticated slope stability modeling with GIS.
Ramakrishnan et al. (2002) has carried out extensive work on landslide analysis
using aerial photographs. Gorsevski et al. (2000a) used logistic regression model
for spatial prediction of landslide hazard. Recently, landslide hazard evaluation
using fuzzy logic, and arti

(1998) carried out terrain classi

cial neural network models have been mentioned in the
various literature of Ercanoglu and Gokceoglu (2020), Pistocchi (2000) and Lee
et al. (2003a, b, 2004a, b). Rowbothan and Dudycha ( 1998 ), Baeza and Corominas
(2001), Lee and Min (2001), Temesgen et al. (2001), Clerici et al. (2002), Donati
and Turrini ( 2002 ), Lee et al. (2002a, b), Rece and Capolongo (2002), Lee and Choi
2003 ), Chung and Fabrri (2003), Lee and Pradhan ( 2006 , 2007 ), Youssef et al.
(2009), and Pradhan and Lee ( 2010a , b , c ) have studied and applied the probabi-
listic model for landslide susceptibility and risk evaluation. Joshi et al. (2002)
carried out landslide hazard zonation in part of Alakananda valley in collaboration